code: def replace_flat_tensors_for_gradients(xs, flat_grads):
      """Replaces Tensors that should be differentiated in `xs` with `flat_grads`.
  
      Args:
        xs: A list of `Tensor`s or `CompositeTensor`s.
        flat_grads: A list of `Tensor`.
  
      Returns:
        A list of `Tensor` or `CompositeTensor`.
      """
      xs_structure = [_get_tensors_for_gradient(x) for x in xs]
      grads = nest.pack_sequence_as(xs_structure, flat_grads)
      return [
          _replace_tensors_for_gradient(x, grad)
          for x, grad in zip(xs, grads)
      ]
  
file_path: tensorflow-upstream/tensorflow/python/framework/composite_tensor_gradient.py
imports: import abc
  import sys
  from tensorflow.python.framework import composite_tensor
  from tensorflow.python.util import nest
label_desc: Use image node_id 4 for calling a global function with example usage: replace_flat_tensors_for_gradients(xs, flat_grads) and returns: unknown